Examples with DoubleStream java.util.stream.DoubleStream used on opensource projects

Example 1 with DoubleStream

use of java.util.stream.DoubleStream in project jdk8u_jdk by JetBrains.

the class StreamSpliteratorTest method testDoubleSplitting.

//
public void testDoubleSplitting() {
    List<Consumer<DoubleStream>> terminalOps = Arrays.asList(s -> s.toArray(), s -> s.forEach(e -> {
    }), s -> s.reduce(Double::sum));
    List<UnaryOperator<DoubleStream>> intermediateOps = Arrays.asList(s -> s.parallel(), // The following ensures the wrapping spliterator is tested
    s -> s.map(i -> i).parallel());
    for (int i = 0; i < terminalOps.size(); i++) {
        Consumer<DoubleStream> terminalOp = terminalOps.get(i);
        setContext("termOpIndex", i);
        for (int j = 0; j < intermediateOps.size(); j++) {
            UnaryOperator<DoubleStream> intermediateOp = intermediateOps.get(j);
            setContext("intOpIndex", j);
            for (boolean proxyEstimateSize : new boolean[] { false, true }) {
                setContext("proxyEstimateSize", proxyEstimateSize);
                // Size is assumed to be larger than the target size for no splitting
                // @@@ Need way to obtain the target size
                Spliterator.OfDouble sp = intermediateOp.apply(IntStream.range(0, 1000).asDoubleStream()).spliterator();
                ProxyNoExactSizeSpliterator.OfDouble psp = new ProxyNoExactSizeSpliterator.OfDouble(sp, proxyEstimateSize);
                DoubleStream s = StreamSupport.doubleStream(psp, true);
                terminalOp.accept(s);
                Assert.assertTrue(psp.splits > 0, String.format("Number of splits should be greater that zero when proxyEstimateSize is %s", proxyEstimateSize));
                Assert.assertTrue(psp.prefixSplits > 0, String.format("Number of non-null prefix splits should be greater that zero when proxyEstimateSize is %s", proxyEstimateSize));
                Assert.assertTrue(psp.sizeOnTraversal < 1000, String.format("Size on traversal of last split should be less than the size of the list, %d, when proxyEstimateSize is %s", 1000, proxyEstimateSize));
            }
        }
    }
}

Example 2 with DoubleStream

use of java.util.stream.DoubleStream in project jdk8u_jdk by JetBrains.

the class SplittableRandomTest method doublesDataProvider.

@DataProvider(name = "doubles")
public static Object[][] doublesDataProvider() {
    List<Object[]> data = new ArrayList<>();
    // Function to create a stream using a RandomBoxedSpliterator
    Function<Function<SplittableRandom, Double>, DoubleStream> rbsf = sf -> StreamSupport.stream(new RandomBoxedSpliterator<>(new SplittableRandom(), 0, SIZE, sf), false).mapToDouble(i -> i);
    // Unbounded
    data.add(new Object[] { TestData.Factory.ofDoubleSupplier(String.format("new SplittableRandom().doubles().limit(%d)", SIZE), () -> new SplittableRandom().doubles().limit(SIZE)), randomAsserter(SIZE, Double.MAX_VALUE, 0d) });
    data.add(new Object[] { TestData.Factory.ofDoubleSupplier(String.format("new SplittableRandom().doubles(%d)", SIZE), () -> new SplittableRandom().doubles(SIZE)), randomAsserter(SIZE, Double.MAX_VALUE, 0d) });
    data.add(new Object[] { TestData.Factory.ofDoubleSupplier(String.format("new RandomBoxedSpliterator(0, %d, sr -> sr.nextDouble())", SIZE), () -> rbsf.apply(sr -> sr.nextDouble())), randomAsserter(SIZE, Double.MAX_VALUE, 0d) });
    for (int b : BOUNDS) {
        for (int o : ORIGINS) {
            final double origin = o;
            final double bound = b;
            data.add(new Object[] { TestData.Factory.ofDoubleSupplier(String.format("new SplittableRandom().doubles(%f, %f).limit(%d)", origin, bound, SIZE), () -> new SplittableRandom().doubles(origin, bound).limit(SIZE)), randomAsserter(SIZE, origin, bound) });
            data.add(new Object[] { TestData.Factory.ofDoubleSupplier(String.format("new SplittableRandom().doubles(%d, %f, %f)", SIZE, origin, bound), () -> new SplittableRandom().doubles(SIZE, origin, bound)), randomAsserter(SIZE, origin, bound) });
            if (origin == 0) {
                data.add(new Object[] { TestData.Factory.ofDoubleSupplier(String.format("new RandomBoxedSpliterator(0, %d, sr -> sr.nextDouble(%f))", SIZE, bound), () -> rbsf.apply(sr -> sr.nextDouble(bound))), randomAsserter(SIZE, origin, bound) });
            }
            data.add(new Object[] { TestData.Factory.ofDoubleSupplier(String.format("new RandomBoxedSpliterator(0, %d, sr -> sr.nextDouble(%f, %f))", SIZE, origin, bound), () -> rbsf.apply(sr -> sr.nextDouble(origin, bound))), randomAsserter(SIZE, origin, bound) });
        }
    }
    return data.toArray(new Object[0][]);
}

Example 3 with DoubleStream

use of java.util.stream.DoubleStream in project jdk8u_jdk by JetBrains.

the class CountTest method testOps.

@Test(dataProvider = "DoubleStreamTestData", dataProviderClass = DoubleStreamTestDataProvider.class)
public void testOps(String name, TestData.OfDouble data) {
    AtomicLong expectedCount = new AtomicLong();
    data.stream().forEach(e -> expectedCount.incrementAndGet());
    withData(data).terminal(DoubleStream::count).expectedResult(expectedCount.get()).exercise();
}

Example 4 with DoubleStream

use of java.util.stream.DoubleStream in project ignite by apache.

the class SplitDataGenerator method testByGen.

/**
 */
<D extends ContinuousRegionInfo> void testByGen(int totalPts, IgniteFunction<ColumnDecisionTreeTrainerInput, ? extends ContinuousSplitCalculator<D>> calc, IgniteFunction<ColumnDecisionTreeTrainerInput, IgniteFunction<DoubleStream, Double>> catImpCalc, IgniteFunction<DoubleStream, Double> regCalc, Ignite ignite) {
    List<IgniteBiTuple<Integer, V>> lst = points(totalPts, (i, rn) -> i).collect(Collectors.toList());
    Collections.shuffle(lst, rnd);
    SparseDistributedMatrix m = new SparseDistributedMatrix(totalPts, featCnt + 1, StorageConstants.COLUMN_STORAGE_MODE, StorageConstants.RANDOM_ACCESS_MODE);
    Map<Integer, List<LabeledVectorDouble>> byRegion = new HashMap<>();
    int i = 0;
    for (IgniteBiTuple<Integer, V> bt : lst) {
        byRegion.putIfAbsent(bt.get1(), new LinkedList<>());
        byRegion.get(bt.get1()).add(asLabeledVector(bt.get2().getStorage().data()));
        m.setRow(i, bt.get2().getStorage().data());
        i++;
    }
    ColumnDecisionTreeTrainer<D> trainer = new ColumnDecisionTreeTrainer<>(3, calc, catImpCalc, regCalc, ignite);
    DecisionTreeModel mdl = trainer.train(new MatrixColumnDecisionTreeTrainerInput(m, catFeaturesInfo));
    byRegion.keySet().forEach(k -> mdl.apply(byRegion.get(k).get(0).features()));
}

Example 5 with DoubleStream

use of java.util.stream.DoubleStream in project ignite by apache.

the class ColumnDecisionTreeTrainerBenchmark method testByGenStreamerLoad.

/**
 */
private void testByGenStreamerLoad(int ptsPerReg, HashMap<Integer, Integer> catsInfo, SplitDataGenerator<DenseLocalOnHeapVector> gen, Random rnd) {
    List<IgniteBiTuple<Integer, DenseLocalOnHeapVector>> lst = gen.points(ptsPerReg, (i, rn) -> i).collect(Collectors.toList());
    int featCnt = gen.featuresCnt();
    Collections.shuffle(lst, rnd);
    int numRegs = gen.regsCount();
    SparseDistributedMatrix m = new SparseDistributedMatrix(numRegs * ptsPerReg, featCnt + 1, StorageConstants.COLUMN_STORAGE_MODE, StorageConstants.RANDOM_ACCESS_MODE);
    IgniteFunction<DoubleStream, Double> regCalc = s -> s.average().orElse(0.0);
    Map<Integer, List<LabeledVectorDouble>> byRegion = new HashMap<>();
    SparseDistributedMatrixStorage sto = (SparseDistributedMatrixStorage) m.getStorage();
    long before = System.currentTimeMillis();
    X.println("Batch loading started...");
    loadVectorsIntoSparseDistributedMatrixCache(sto.cache().getName(), sto.getUUID(), gen.points(ptsPerReg, (i, rn) -> i).map(IgniteBiTuple::get2).iterator(), featCnt + 1);
    X.println("Batch loading took " + (System.currentTimeMillis() - before) + " ms.");
    for (IgniteBiTuple<Integer, DenseLocalOnHeapVector> bt : lst) {
        byRegion.putIfAbsent(bt.get1(), new LinkedList<>());
        byRegion.get(bt.get1()).add(asLabeledVector(bt.get2().getStorage().data()));
    }
    ColumnDecisionTreeTrainer<VarianceSplitCalculator.VarianceData> trainer = new ColumnDecisionTreeTrainer<>(2, ContinuousSplitCalculators.VARIANCE, RegionCalculators.VARIANCE, regCalc, ignite);
    before = System.currentTimeMillis();
    DecisionTreeModel mdl = trainer.train(new MatrixColumnDecisionTreeTrainerInput(m, catsInfo));
    X.println("Training took: " + (System.currentTimeMillis() - before) + " ms.");
    byRegion.keySet().forEach(k -> {
        LabeledVectorDouble sp = byRegion.get(k).get(0);
        Tracer.showAscii(sp.features());
        X.println("Predicted value and label [pred=" + mdl.apply(sp.features()) + ", label=" + sp.doubleLabel() + "]");
        assert mdl.apply(sp.features()) == sp.doubleLabel();
    });
}